class museotoolbox.cross_validation.SpatialLeaveOneSubGroupOut(distance_thresold, distance_matrix, distance_label, random_state=False, verbose=False)[source]

Generate a Cross-Validation with Spatial Leave-One-Out method.

  • distance_matrix (numpy.ndarray, shape [n_samples, n_samples]) – Array got from function museotoolbox.vector_tools.get_distance_matrix()

  • distance_thresold (int.) – In pixels.

  • distance_label (None or array.) – If array, got from function museotoolbox.vector_tools.get_distance_matrix()

  • random_state (integer or None, optional (default=None)) – If int, random_state is the seed used by the random number generator; If None, the random number generator is created with time.time().

  • verbose (integer or False, optional (default=False)) – Controls the verbosity: the higher the value is, the more the messages are detailed.

See also


to get distance matrix and label.

Manage cross-validation methods to generate the duo valid/train samples.


__init__(distance_thresold, distance_matrix, …)

Manage cross-validation methods to generate the duo valid/train samples.

get_n_splits([X, y, groups])

Returns the number of splitting iterations in the cross-validator.



save_to_vector(vector, field[, group, …])

Save to vector files each fold from the cross-validation.

split(X, y[, groups])

Split the vector/array according to y and groups.

Examples using museotoolbox.cross_validation.SpatialLeaveOneSubGroupOut